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Updated: Jun 9, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Predictors of competing mortality in early breast cancer
Loren K Mell1, Jong-Hyeon Jeong, Michael A Nichols
1Department of Radiation Oncology, University of California San Diego/Moores Cancer Center, La Jolla, California 92129, USA. lmell@ucsd.edu
Background:
Death in the absence of disease recurrence (competing mortality) is an important determinant of disease-free survival (DFS) in early breast cancer. The authors sought to identify predictors of this event using competing risks modeling.
Methods:
A cohort study was made of 1231 consecutive women with stage I to II invasive breast cancer diagnosed between 1986 and 2004, treated with breast conservation therapy. Median follow-up was 82 months. The authors used a parametric competing risks regression model to analyze factors associated with the cumulative incidence of competing mortality. They generated a risk score from the model coefficient estimates and stratified patients according to low and high risk score for analysis.
Results:
Ten-year DFS was 69.7% (95% confidence interval [CI], 66.2%-72.9%). The 10-year cumulative incidence of locoregional recurrence (LRR) was 4.4% (95% CI, 3.0%-5.8%), distant recurrence was 7.1% (95% CI, 5.4%-8.9%), and competing mortality was 18.7% (95% CI, 15.9%-21.6%). On multivariate analysis, competing mortality was associated with increasing age (hazard ratio [HR], 1.83 per 10 years; 95% CI, 1.58-2.12), black race (HR, 1.71; 95% CI, 1.17-2.51), and comorbid disease (HR, 1.93, 95% CI, 1.40-2.65). Ten-year cumulative incidences of competing mortality, locoregional recurrence, and distant recurrence for patients at low (n=638) versus high (n=593) risk of competing mortality were 7.2% versus 30.6% (P<.001), 4.4% versus 4.4% (P=.97), and 8.6% versus 5.6% (P=.12), respectively.
Conclusions:
Competing mortality is an important event influencing 10-year DFS in early breast cancer and is associated with increasing age, black race, and comorbid disease. Stratifying patients according to competing mortality risk may be useful in designing clinical trials.
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